Most pharmacogenetic strategies to date have focused on the role of single genes in the regulation of drug activity and have made important steps towards the goal of optimizing therapy for individual patients. However, there is clear evidence that medication responses, like most common diseases, are under the control of a network of genes, each contributing to the patient's phenotype. The CREATE Pharmacogenetic Research Network (Comprehensive Research on Expressed Alleles in Therapeutic Evaluation) was initially funded in 2001 and has consistently been a productive member ofthe NIH Pharmacogenetics Research Network (PGRN). CREATE has made significant contributions to the PGRN goals of publicly available pharmacogenetic data, shared computational and analytical resources, defining the common goals and needs for the field, implementing high impact collaborative initiatives, and communicating PGRN finding to foster translation and application of pharmacogenetic knowledge. CREATE brings together infrastructure for the evaluation of pathways regulating drug activity. This is achieved through the coordinated efforts of investigators from the University of North Carolina Institute for Pharmacogenomics and Individualized Therapy, Washington University, North Carolina State University, Duke, and the Hamner Institutes with expertise in the fields of Genomics, Pharmacogenetics, Clinical Pharmacology, Bioinformatics, Computational Biology, Statistical Genetics, Population Genetics, Systems Biology, and Translational Research. Together they will evaluate the following general aims to develop validation strategies for applied pharmacogenetics. 1) Functionally assess, and clinically validate existing drug pathways, and extend our knowledge of drug pathways with new discoveries based on genome and transcriptome-wide approaches;2) Evaluate novel statistical and molecular approaches to pathway dissection and validation;3) Identify genetic variation in members of drug pathways, and evaluate the relevance of this variation of clinical responses to drugs;and 4) Provide a PGRN resource forthe application of massively parallel resequencing. Supported by Administrative, Bioinformatic/ Biostatistical and Cellular Phenotyping cores, these aims are being achieved using human cancer as the primary model system, as it is a common cause of death, has no clear prognostic tools to guide therapy, and is treated with a small number of toxic and erratically effective medications. This approach allows us to continue to make strong progress in understanding genes that influence pharmacologic response.